Agricultural productivity in past societies

Toward an empirically informed model for testing cultural evolutionary hypotheses

Datos Bibliográficos

ID13100830
AutoresThomas E Currie (0000-0001-9861-1341, University of Exeter, autor de correspondencia), Amy Bogaard (0000-0002-6716-8890, University of Oxford), Rudolf Cesaretti (0000-0002-7003-1211, Arizona State University), Neil R Edwards (0000-0001-6045-8804, The Open University), Pieter François (0000-0002-1590-0509, University of Hertfordshire), Philip B Holden (0000-0002-2369-0062, The Open University), Daniel Hoyer (0000-0003-2675-257X, The Evolution Institute), Andrey Korotayev (0000-0003-3014-2037, Russian Academy of Sciences), J W Manning (Yale University), Juan Carlos Moreno García (0000-0002-8045-3274), Oluwole Oyebamiji (0000-0002-6561-9459, The Open University), C A Petrie (0000-0002-2926-7230, University of Cambridge), Peter Turchin (0000-0002-1292-8100, The Evolution Institute), H Whitehouse (0000-0001-6935-6724, University of Oxford), Alice Williams (0009-0002-4768-6698, University of Exeter)
Año2015
Volumen6
Número1
Fecha de publicación2015-07-04
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaCliodynamics The Journal of Quantitative History and Cultural Evolution (JOURNAL)
Identificadores de la revistaISSN: 2373-7530 • E-ISSN: 2373-7530
EditorialCalifornia Digital Library (CDL) (PUBLISHER)
DOI10.21237/c7clio6127473
OpenAlexW1860480686
IdiomaEN
Citas recibidas11
Referencias citadas46

Agricultural productivity, and its variation in space and time, plays a fundamental role in many theories of human social evolution. However, we often lack systematic information about the productivity of past agricultural systems on a large enough scale in order to be able to test these theories properly. The effect of climate on crop yields has received a great deal of attention resulting in a range of empirical and process-based models, yet the focus has primarily been on current or future conditions. In this paper, we argue for a “bottom-up” approach that estimates productivity, or potential productivity based on information about the agricultural practices and technologies used in past societies. Of key theoretical interest is using this information to estimate the carrying capacity of a given region, independently of estimates of population size. We outline how explicit crop yield models can be combined with high quality historical and archaeological information about past societies, in order to infer the temporal and geographic patterns of change in agricultural productivity and potential. We discuss the kinds of information we need to collect about agricultural techniques and practices in the past, and introduce a new databank initiative we have developed for collating the best available historical and archaeological evidence. A key benefit of our approach lies in making explicit the steps in the process of estimating past productivities and carrying capacities, and in being able to assess the effects of different modelling assumptions. This is undoubtedly an ambitious task, yet promises to provide important insights into fundamental aspects of past societies, and will enable us to test more rigorously key hypotheses about human socio-cultural evolution

Agricultural productivity · Agriculture · Data science · Economic growth · Economics · Environmental resource management · Epistemology · Geography · Management science · Population · Process (computing · Productivity · Quality (philosophy · Sociology · Archaeology and ancient environmental studies · Computer Science · Pacific and Southeast Asian Studies · Pleistocene-Era Hominins and Archaeology